Adnan Mohsin Abdulazeez

Duhok Polytechnic University | DPU · Presidency

Finger vein biometrics is one of the most promising ways to identify a person because it can provide uniqueness, protection against forgery, and bioassay. Due to the limitations of the imaging environments, however, the finger vein images that are taken can quickly become low-contrast, blurry, and very noisy. Therefore, more robust and relevant fea...

Metaheuristic algorithms are becoming powerful methods for solving continuous global optimization and engineering problems due to their flexible implementation on the given problem. Most of these algorithms draw their inspiration from the collective intelligence and hunting behavior of animals in nature. This paper proposes a novel metaheuristic al...

Information-based image processing and computer vision methods are utilized in several healthcare organizations to diagnose diseases. The irregularities in the visual system are identified over fundus images shaped over a fundus camera. Among ophthalmology diseases, glaucoma is measured as the most common case that can lead to neurodegenerative ill...

The developing of deep learning systems that used for chronic diseases diagnosing is challenge. Furthermore, the localization and identification of objects like white blood cells (WBCs) in leukemia without preprocessing or traditional hand segmentation of cells is a challenging matter due to irregular and distorted of nucleus. This paper proposed a...

In the last decade, the Facial Expression Recognition field has been studied widely and become the base for many researchers, and still challenging in computer vision. Machine learning technique used in facial expression recognition facing many problems, since human emotions expressed differently from one to another. Nevertheless, Deep learning tha...

Digital watermarking is getting more research and industry attention. Digital multimedia data allows for robust and simple data editing and modification. However, the spread of digital media presents concerns for digital content owners. It is important to note that digital data can be copied without quality or content loss. This has a considerable...

Machine learning and data mining have established several effective applications in gene selection analysis. This paper review semi-supervised learning algorithms and gene selection. Semi-Supervised learning is learning that includes experiences that are familiar with the environment because it can deal with labeled and unnamed data. Gene selection...

The rapid development of technology reveals several safety concerns for making life more straightforward. The advance of the Internet over the years has increased the number of attacks on the Internet. The IDS is one supporting layer for data protection. Intrusion Detection Systems (IDS) offer a healthy market climate and prevent misgivings in the...

Multi-label classification addresses the issues that more than one class label assigns to each instance. Many real-world multi-label classification tasks are high-dimensional due to digital technologies, leading to reduced performance of traditional multi-label classifiers. Feature selection is a common and successful approach to tackling this prob...

The importance of the plant for the human being and the environment led to deeply been studied and classified in detail. The advancement of the technology is the main factor in finding many ways for plant identification process. Some kind of initial intelligence systems in order to identify plant, followed by many theories and concepts using method...

Prediction is vital in our daily lives, as it is used in various ways, such as learning, adapting, predicting, and classifying. The prediction of parameters capacity of RNNs is very high; it provides more accurate results than the conventional statistical methods for prediction. The impact of a hierarchy of recurrent neural networks on Predicting p...

Machine learning algorithms have been used in many fields, like economics, medicine, etc. Education data mining is one of the areas concerned with exploring patterns of data in an educational environment. One of the most important uses is to predict students' performance to improve the existing educational situation. It can be considered as one of...

Data Mining is the process of finding knowledge through the processing of massive amounts of data from different viewpoints and combining them into valuable information; data mining has been a crucial part in various aspects of human life. It is used to recognize the covered up patterns in a huge amount of data. Classification methods are supervise...

Internet of Things (IoT) systems usually produce massive amounts of data, while the number of devices connected to the internet might reach billions by now. Sending all this data over the internet will overhead the cloud and consume bandwidth. Fog Computing's (FC) promising technology can solve the issue of computing and networking bottlenecks in l...

Multi-label classification is the process of specifying more than one class label for each instance. The high-dimensional data in various multi-label classification tasks have a direct impact on reducing the e ciency of traditional multi-label classifiers. To tackle this problem, feature selection is used as an effective approach to retain relevant...

The bird classifier is a system that is equipped with an area machine learning technology and uses a machine learning method to store and classify bird calls. Bird species can be known by recording only the sound of the bird, which will make it easier for the system to manage. The system also provides species classification resources to allow autom...

Leukemia refers to a disease that affects the white blood cells (WBC) in the bone marrow and/or blood. Blood cell disorders are often detected in advanced stages as the number of cancer cells is much higher than the number of normal blood cells. Identifying malignant cells is critical for diagnosing leukemia and determining its progression. This pa...

Weather forecasting is the process of predicting the status of the atmosphere for certain regions or locations by utilizing recent technology. Thousands of years ago, humans tried to foretell the weather state in some civilizations by studying the science of stars and astronomy. Realizing the weather conditions has a direct impact on many fields, s...

Web of thing (WoT) is a gifted answer for interface and access each gadget through the web. Consistently the gadget includes increments with huge variety fit as a fiddle, size, use and intricacy. In this paper Since WoT drives the world and changes individuals' lives with its wide scope of administrations and applications. In any case, WoT offers v...

Review Thanks

Whether you deal with a real-life issue or create a software product, optimization is constantly the ultimate goal. This goal, however, is achieved by utilizing one of the optimization algorithms. The progressively popular Gradient Descent (GD) optimization algorithms are frequently used as black box optimizers when solving unrestricted problems of...

Biometric authentication is one of the most quickly increasing innovations in today's world; this promising technology has seen widespread use in a variety of fields, including surveillance services, safe financial transfers, credit-card authentication. in biometric verification processes such as gender, age, ethnicity is iris recognition technolog...

Artificial Neural Networks (ANNs) are modern computing methods that have been used extensively in solving many complicated problems in the physical world. The attractiveness of ANNs stems from its remarkable data processing features, which mainly related to high parallelism, fault and noise resistance, learning and widespread abilities of nonlinear...

Lung cancer is one of the leading causes of mortality in every country, affecting both men and women. Lung cancer has a low prognosis, resulting in a high death rate. The computing sector is fully automating it, and the medical industry is also automating itself with the aid of image recognition and data analytics. This paper endeavors to inspect a...

Early diagnosis is considered important for medical images of breast cancer, the rate of recovery and safety of affected women can be improved. It is also assisting doctors in their daily work by creating algorithms and software to analyze the medical images that can identify early signs of breast cancer. This review presents a comparison has been...

Breast cancer is one of the most common diseases among women, accounting for many deaths each year. Even though cancer can be treated and cured in its early stages, many patients are diagnosed at a late stage. Data mining is the method of finding or extracting information from massive databases or datasets, and it is a field of computer science wit...

In December 2019, a novel coronavirus, now named SARS-CoV-2, caused a series of acute atypical respiratory diseases in Wuhan, Hubei province, China. It triggered several acute atypical respiratory diseases. COVID-19 was the name given to the virus's disease. The infection is human-to-human transmissible, and it has triggered a global pandemic. Vacc...

Diabetes may be predicted and prevented by exploring critical diabetes characteristics by computational data extraction methods. This study proposed a system biology approach to the pathogenic process to identify essential biomarkers as drug targets. The fact that disease recognition and investigation require many details, data mining plays a criti...

In December 2019, a novel coronavirus, now named SARS-CoV-2, caused a series of acute atypical respiratory diseases in Wuhan, Hubei province, China. It triggered several acute atypical respiratory diseases. COVID-19 was the name given to the virus's disease. The infection is human-to-human transmissible, and it has triggered a global pandemic. Vacc...

The agriculture importance is not restricted to our daily life; it is also an effective field that enhances the economic growth in any country. Therefore, developing the quality of the crop yields using recent technologies is a crucial procedure to obtain competitive crops. Nowadays, data mining is an emerging research field in agriculture especial...

One of the main factors that assist to increase the growth of any country is Agriculture. The detection of diseases from plant leaf images is one of the most important fields of agricultural research. To identify disease factors, this field requires a reliable prediction approach. Data Mining (DM) is the process of analyzing data from different asp...

The development of machine learning systems that used for diagnosis of chronic diseases is challenging mainly due to lack of data and difficulty of diagnosing. This paper compared between two proposed systems for computer-aided diagnosis (CAD) to detect and classify three types of white blood cells which are fundamental of an acute leukemia diagnos...

A major cause of human vision loss worldwide is Diabetic retinopathy (DR). The disease requires early screening for slowing down the progress. However, in low-resource settings where few ophthalmologists are available to care for all patients with diabetes, the clinical diagnosis of DR will be a considerable challenge. This paper reviews the most r...

Semi-supervised learning is the class of machine learning that deals with the use of supervised and unsupervised learning to implement the learning process. Conceptually placed between labelled and unlabeled data. In certain cases, it enables the large numbers of unlabeled data required to be utilized in comparison with usually limited collections...

Writer identification (WI) based on handwritten text structures is typically focused on digital characteristics, with letters/strokes representing the information acquired from the current research in the integration of individual writing habits/styles. Previous studies have indicated that a word's attributes contribute to greater recognition than...

Classification is the most widely applied machine learning problem today, with implementations in face recognition, flower classification, clustering, and other fields. The goal of this paper is to organize and identify a set of data objects. The study employs K-nearest neighbors, decision tree (j48), and random forest algorithms, and then compares...

Rapid changes are occurring in our global ecosystem, and stresses on human well-being, such as climate regulation and food production, are increasing, soil is a critical component of agriculture. The project aims to use Data Mining (DM) classification techniques to predict soil data. Analysis DM classification strategies such as k-Nearest-Neighbors...

In December 2019, SARS-CoV-2 caused coronavirus disease (COVID-19) distributed to all countries, infecting thousands of people and causing deaths. COVID-19 induces mild sickness in most cases, although it may render some people very ill. Therefore, vaccines are in various phases of clinical progress, and some of them being approved for national use...

Extending technologies and data development culminated in the need for quicker and more reliable processing of massive data sets. Machine Learning techniques are used excessively. This paper, therefore, attempts to deal with data processing, using a support vector machine (SVM) algorithm in different fields since it is a reliable, efficient classif...

Medical image segmentation plays an essential role in computer-aided diagnostic systems in various applications. Therefore, researchers are attracted to apply new algorithms for medical image processing because it is a massive investment in developing medical imaging methods such as dermatoscopy, X-rays, microscopy, ultrasound, computed tomography...

Image compression is an essential technology for encoding and improving various forms of images in the digital era. The inventors have extended the principle of deep learning to the different states of neural networks as one of the most exciting machine learning methods to show that it is the most versatile way to analyze, classify, and compress im...

Extending technologies and data development culminated in the need for quicker and more reliable processing of massive data sets. Machine Learning techniques are used excessively. This paper, therefore, attempts to deal with data processing, using a support vector machine (SVM) algorithm in different fields since it is a reliable, efficient classif...

Medical image segmentation plays an essential role in computer-aided diagnostic systems in various applications. Therefore, researchers are attracted to apply new algorithms for medical image processing because it is a massive investment in developing medical imaging methods such as dermatoscopy, X-rays, microscopy, ultrasound, computed tomography...

The writer identification (WI) of handwritten Arabic text is now of great concern to intelligence agencies following the recent attacks perpetrated by known Middle East terrorist organizations. It is also a useful instrument for the digitalization and attribution of old text to other authors of historic studies , including old national and religiou...

Facial attractiveness or facial beauty prediction (FBP) is a current study that has several potential usages. It is a key difficulty area in the computer vision domain because of the few public databases related to FBP and its experimental trials on the minor-scale database. Moreover, the evaluation of facial beauty is personalized in nature, wi...

Facial emotional processing is one of the most important activities in effective calculations, engagement with people and computers, machine vision, video game testing, and consumer research. Facial expressions are a form of nonverbal communication, as they reveal a person's inner feelings and emotions. Extensive attention to Facial Expression Reco...

Intrusion detection is one of the most critical network security problems in the technology world. Machine learning techniques are being implemented to improve the Intrusion Detection System (IDS). In order to enhance the performance of IDS, different classification algorithms are applied to detect various types of attacks. Choosing a suitable clas...

Big databases are increasingly widespread and are therefore hard to understand, in exploratory biomedicine science, big data in health research is highly exciting because data-based analyses can travel quicker than hypothesis-based research. Principal Component Analysis (PCA) is a method to reduce the dimensionality of certain datasets. Improves in...

Today, there are different types of self-controlled robots. Some of them had critical effects on our lives like industrial and medical robots. Others are for military usages such as drones and the pets robots just for entertainment. The crucial differences between this kind of robot and the controlled ones are their ability to move on their own and...

Decision tree classifiers are regarded to be a standout of the most well-known methods to data classification representation of classifiers. Different researchers from various fields and backgrounds have considered the problem of extending a decision tree from available data, such as machine study, pattern recognition, and statistics. In various fi...

Nowadays, machine learning algorithms have become very important in the medical sector, especially for diagnosing disease from the medical database. Many companies using these techniques for the early prediction of diseases and enhance medical diagnostics. The motivation of this paper is to give an overview of the machine learning algorithms that a...

Disasters could cause communication systems to partially or completely down. In such a case, relief operations need a rapidly deployed communication system to save lives. Exchanging information among the rescue team is a vital factor to make important decisions. Communication system required to be robust to failures, rapidly deployable, easily main...

This paper suggests a new internal architecture of holon based on feature selection model using the combination of Bees Algorithm (BA) and Artificial Neural Network (ANN). BA is used to generate features while ANN is used as a classifier to evaluate the produced features. Proposed system is applied on the Wine dataset, the statistical result proves...

Disasters could cause communication systems to partially or completely down. In such a case, relief operations need a rapidly deployed communication system to save lives. Exchanging information among the rescue team is a vital factor to make important decisions. Communication system re�quired to be robust to failures, rapidly deployable, easily...

The techniques of machine learning are commonly used in classifying breast lesions, as they can improve the mammogram accuracy in detecting malignant masses. One of the top causes of death for women remains breast cancer. Early diagnosis can facilitate adequate treatment and reduce morbidity and mortality. Screening for cancer via mammogram can be...